The Recommendations tab serves as ServiceAI's strategic improvement engine, transforming analytical insights into concrete, actionable tasks designed to systematically enhance service desk performance and AI deployment readiness.
This section provides MSPs with both AI-generated and manually created action items that convert raw performance data into specific improvement initiatives across documentation, training, processes, and technology.
- Recommendation Management for Continuous Service Desk Improvement
- Understanding the Recommendations Grid
- Understanding Individual Recommendations
- Understanding Recommendation Categories
- Available Actions and Business Impact
Recommendation Management for Continuous Service Desk Improvement
The Recommendations tab bridges the gap between ServiceAI's data analysis and actual service desk improvements. In short, it's where the rubber of insights meets the road of tangible actions.
Rather than simply showing what's wrong through RPS scores, it provides specific, prioritized steps to systematically address identified issues and opportunities.
Enable Systematic Service Desk Enhancement
- Recommendation management converts scattered improvement ideas into organized, trackable initiatives that can be prioritized, assigned, and measured for impact on overall service desk performance and AI deployment readiness.
Support Strategic Planning and Resource Allocation
- By categorizing and prioritizing recommendations, MSPs can make informed decisions about where to invest time, training resources, and process changes to achieve the greatest impact on service quality and automation readiness.
Accelerate AI Deployment Through Targeted Improvements
- Recommendations directly target the factors that improve Ticket RPS (better documentation), Agent RPS (training and process improvements), and User RPS (enhanced service delivery methods), creating a clear path from current performance to AI-ready operations.
Understanding the Recommendations Grid
The main recommendations grid displays all improvement suggestions generated by ServiceAI or manually created by your team, organized by category, status, and priority to provide clear visibility into your service desk enhancement roadmap.
About the Recommendation Grid Columns
The recommendation grid columns are not customizable. They include the following:
- Created: The date that the recommendation was created within ServiceAI.
- Title: The subject and general purpose of the recommendation.
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Status: The current color-coded state of the recommendation, including:
- New (blue)
- In Progress (yellow)
- Will Not Implement (gray)
- Implemented (green)
- Category: The type of recommendation divided by a categorical label. Organizing recommendations by type can help internal agents divide work based on strength (some agents may be better suited for documentation improvements, or perhaps some have access to change processes, while others don't). AI-generated recommendations will automatically have their category applied by the AI's best judgment. The categories are further explained in the following section.
- Implemented: The date that the recommendation was implemented. This can show progress and help organize teams to tackle recommendations according to the overall agent workload.
Understanding Individual Recommendations
Selecting a specific recommendation will expand it to show the full details of the recommended task. Generally speaking, acting on these recommendations will have both a tangible effect (by way of RPS scores) and an intangible effect of improving the service desk.
Recommendation Best Practice: AI recommendations can range from being very specific to being very narrow. As a best practice, focus your efforts on the recommendations that make the biggest impact on the team, the customers, and the business before focusing on
Available Actions on Individual Recommendations
On an individual recommendation, agents have the following actions that they can take:
- Share: Share this recommendation by email or in-app task for someone to look into and decide on how to proceed with it.
- Edit: Change the recommendation title, body, status, category, and implementation date.
- Add Article: Add the content of the recommendation to a piece of documentation. The AI will do its best to source relevant tickets and information, but this is best supplemented by a human agent to further improve the relevance and usefulness of the document.
- Delete: Delete the recommendation.
Understanding Recommendation Categories
Recommendation categories help keep the recommendations focused on key areas that drive service desk improvement.
Documentation Improvements
Recommendations targeting knowledge base gaps and article quality issues that directly impact Ticket RPS scores and AI deployment readiness.
Common Examples: Create articles for frequently occurring ticket types with low AI confidence, improve article readability scores for better AI comprehension, and consolidate overlapping documentation that confuses AI responses.
Strategic Impact: Directly improves AI deployment readiness by addressing the knowledge foundation necessary for automated support success.
Agent Training Initiatives
Suggestions for skills development and coaching opportunities based on Agent RPS analysis and performance patterns.
Common Examples: Provide communication training for agents with low customer satisfaction scores, develop technical expertise in areas with frequent escalations, and implement mentoring programs for junior technicians.
Strategic Impact: Enhances service quality while preparing agents for higher-value work as AI handles routine tasks.
Process Change Recommendations
Workflow optimization and procedural improvements that address systemic service delivery issues.
Common Examples: Implement standardized escalation procedures, create client onboarding checklists, and establish proactive communication protocols for high-priority tickets.
Strategic Impact: Improves overall service consistency and efficiency while creating frameworks that support AI integration.
Product Change Suggestions
System or tool modifications that could enhance service desk capabilities and user experience.
Common Examples: Integrate additional monitoring tools, implement automated ticket routing based on expertise, and enhance client portal functionality for self-service options.
Strategic Impact: Supports long-term service desk evolution and creates infrastructure for advanced AI deployment.
Other Operational Enhancements
Miscellaneous improvements that don't fit standard categories but could impact service desk performance.
Common Examples: Office environment improvements, team communication enhancements, client relationship management initiatives.
Strategic Impact: Addresses holistic factors that contribute to team performance and client satisfaction.
Available Actions and Business Impact
ServiceAI provides several recommendation management tools that transform improvement ideas into systematic organizational enhancement.
Generate AI-Powered Recommendations
Create data-driven improvement suggestions based on comprehensive service desk analysis:
How to Use: Click Generate AI Recommendation to analyze accumulated ticket data, documentation gaps, agent performance patterns, and user satisfaction trends to automatically surface improvement opportunities.
Business Impact: Identifies optimization opportunities that might otherwise be overlooked, ensures recommendations are based on actual data rather than assumptions, and provides objective prioritization for improvement efforts.
Create Manual Recommendations
Add custom improvement ideas based on team observations and strategic initiatives:
How to Use: Use manual recommendation creation to document team-identified opportunities, strategic initiatives, or improvements suggested by clients or stakeholders.
Business Impact: Ensures all improvement ideas are captured and tracked systematically, enables collaborative improvement planning, and maintains visibility into both data-driven and intuitive enhancement opportunities.
Track Implementation Progress
Monitor recommendation completion and measure impact on service desk performance:
How to Use: Update recommendation status through the implementation lifecycle (New → In Progress → Implemented or Will Not Implement) while documenting completion details and impact measurements.
Business Impact: Enables accountability for improvement initiatives, supports measurement of enhancement impact on RPS scores and service quality, and provides a historical record of organizational development efforts.
Generate Supporting Documentation
Create articles directly from recommendations to address identified knowledge gaps:
How to Use: Use the direct article generation functionality within recommendations to immediately create documentation that addresses identified gaps or process improvements.
Business Impact: Accelerates implementation of documentation-related recommendations, ensures consistent quality of generated content, and directly improves Ticket RPS scores through targeted knowledge base enhancements.
Share and Assign Recommendations
Distribute improvement initiatives across team members for collaborative implementation:
How to Use: Use sharing and assignment features to delegate specific recommendations to appropriate team members, set deadlines, and coordinate collaborative improvement efforts.
Business Impact: Enables distributed implementation of improvements, ensures appropriate expertise is applied to specific recommendation types, and maintains accountability through clear ownership and tracking.
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